Triple
T1688623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ola Cabs |
E36498
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object | Ankit Bhati |
E192549
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ankit Bhati | Statement: [Ola Cabs, foundedBy, Ankit Bhati]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ankit Bhati Context triple: [Ola Cabs, foundedBy, Ankit Bhati]
-
A.
Ankit Bhati
chosen
Ankit Bhati is an Indian entrepreneur best known as the co-founder and former Chief Technology Officer of the ride-hailing company Ola.
-
B.
Bhavish Aggarwal
Bhavish Aggarwal is an Indian entrepreneur best known for co-founding and leading the ride-hailing and mobility company Ola.
-
C.
Sachit Mehra
Sachit Mehra is a Canadian political figure who serves in a top leadership role within the Liberal Party of Canada.
-
D.
Krishna Bharadwaj
Krishna Bharadwaj was an influential Indian economist known for her work in classical political economy and development economics, and for her role in shaping economic thought and teaching in India.
-
E.
Nishant
Nishant is a critically acclaimed 1975 Indian parallel cinema film directed by Shyam Benegal that explores themes of feudal oppression and social injustice in rural India.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a886151508819084fa7f1ce6e05577 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa6296655c8190835ec0d20f7460ca |
completed | March 6, 2026, 5:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5b9be4481908c0b6f030889edfb |
completed | March 8, 2026, 5:45 p.m. |
Created at: March 4, 2026, 7:29 p.m.